a Probabilistic Cooperation Between Trackers of Coupled Objects

Ido Leichter, Michael Lindenbaum, and Ehud Rivlin.
A probabilistic cooperation between trackers of coupled objects.
In ICIP, 1045-1048, 2004

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Abstract

Much work has been done in the field of visual object tracking, yielding a wide range of trackers, including ones aimed for multiple objects. In many cases, there may be a coupling between simultaneously cracked objects, e.g., the locations of some person's eyes. In such cases, tracking each object independently, or using any multi-target tracker ignoring this coupling, will he suboptimal. This paper addresses these cases, and takes advantage of the coupling between the tracked objects to enhance the tracking performance. An analytically justified, probabilistic framework for cooperating between the individual trackers is suggested. The framework is fairly general, allowing to cooperate between any two trackers which output a probability density function of the tracked state, even when the objects are tracked in different state spaces. The framework is successfully tested on two different kinds of trackers, showing the benefit gained from the coupling exploitation.

Co-authors

Bibtex Entry

@inproceedings{LeichterLR04i-a,
  title = {A probabilistic cooperation between trackers of coupled objects.},
  author = {Ido Leichter and Michael Lindenbaum and Ehud Rivlin},
  year = {2004},
  booktitle = {ICIP},
  pages = {1045-1048},
  abstract = {Much work has been done in the field of visual object tracking, yielding a wide range of trackers, including ones aimed for multiple objects. In many cases, there may be a coupling between simultaneously cracked objects, e.g., the locations of some person's eyes. In such cases, tracking each object independently, or using any multi-target tracker ignoring this coupling, will he suboptimal. This paper addresses these cases, and takes advantage of the coupling between the tracked objects to enhance the tracking performance. An analytically justified, probabilistic framework for cooperating between the individual trackers is suggested. The framework is fairly general, allowing to cooperate between any two trackers which output a probability density function of the tracked state, even when the objects are tracked in different state spaces. The framework is successfully tested on two different kinds of trackers, showing the benefit gained from the coupling exploitation.}
}